{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1.加载库"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "import math\n",
    "import toad\n",
    "import matplotlib\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import xgboost as xgb\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.metrics import roc_auc_score, roc_curve, auc\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from toad.plot import bin_plot, badrate_plot\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from toad.metrics import KS, F1, AUC\n",
    "from toad.scorecard import ScoreCard \n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2.加载数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 加载数据\n",
    "data_all = pd.read_csv('../data/scorecard.txt')\n",
    "\n",
    "# 指定不参与训练列名\n",
    "ex_list = ['uid', 'samp_type', 'bad_ind']\n",
    "# 参与训练列名\n",
    "ft_list = data_all.columns.tolist()\n",
    "for col in ex_list:\n",
    "    ft_list.remove(col)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.划分开发样本、验证样本与时间外样本"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "dev = data_all[(data_all['samp_type'] == 'dev')]\n",
    "val = data_all[(data_all['samp_type'] == 'val')]\n",
    "off = data_all[(data_all['samp_type'] == 'off')]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4.探索性数据分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>type</th>\n",
       "      <th>size</th>\n",
       "      <th>missing</th>\n",
       "      <th>unique</th>\n",
       "      <th>mean_or_top1</th>\n",
       "      <th>std_or_top2</th>\n",
       "      <th>min_or_top3</th>\n",
       "      <th>1%_or_top4</th>\n",
       "      <th>10%_or_top5</th>\n",
       "      <th>50%_or_bottom5</th>\n",
       "      <th>75%_or_bottom4</th>\n",
       "      <th>90%_or_bottom3</th>\n",
       "      <th>99%_or_bottom2</th>\n",
       "      <th>max_or_bottom1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>bad_ind</th>\n",
       "      <td>float64</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.00%</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0187671</td>\n",
       "      <td>0.135702</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>uid</th>\n",
       "      <td>object</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.00%</td>\n",
       "      <td>95806</td>\n",
       "      <td>A14795869:0.00%</td>\n",
       "      <td>A9676154:0.00%</td>\n",
       "      <td>A8747039:0.00%</td>\n",
       "      <td>A11068305:0.00%</td>\n",
       "      <td>A3268951:0.00%</td>\n",
       "      <td>A2095231:0.00%</td>\n",
       "      <td>A2007149:0.00%</td>\n",
       "      <td>A14790772:0.00%</td>\n",
       "      <td>A396461:0.00%</td>\n",
       "      <td>A5226432:0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>td_score</th>\n",
       "      <td>float64</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.00%</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.499739</td>\n",
       "      <td>0.288349</td>\n",
       "      <td>5.46966e-06</td>\n",
       "      <td>0.00961341</td>\n",
       "      <td>0.0997056</td>\n",
       "      <td>0.500719</td>\n",
       "      <td>0.747984</td>\n",
       "      <td>0.900024</td>\n",
       "      <td>0.990041</td>\n",
       "      <td>0.999999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>jxl_score</th>\n",
       "      <td>float64</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.00%</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.499338</td>\n",
       "      <td>0.28885</td>\n",
       "      <td>1.28155e-05</td>\n",
       "      <td>0.00994678</td>\n",
       "      <td>0.0991025</td>\n",
       "      <td>0.499795</td>\n",
       "      <td>0.748646</td>\n",
       "      <td>0.899703</td>\n",
       "      <td>0.989348</td>\n",
       "      <td>0.999985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mj_score</th>\n",
       "      <td>float64</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.00%</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.50164</td>\n",
       "      <td>0.288679</td>\n",
       "      <td>6.92442e-06</td>\n",
       "      <td>0.0105076</td>\n",
       "      <td>0.100882</td>\n",
       "      <td>0.503048</td>\n",
       "      <td>0.752032</td>\n",
       "      <td>0.899308</td>\n",
       "      <td>0.990047</td>\n",
       "      <td>0.999993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rh_score</th>\n",
       "      <td>float64</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.00%</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.498407</td>\n",
       "      <td>0.287797</td>\n",
       "      <td>5.00212e-06</td>\n",
       "      <td>0.00991632</td>\n",
       "      <td>0.0999483</td>\n",
       "      <td>0.497466</td>\n",
       "      <td>0.747188</td>\n",
       "      <td>0.899286</td>\n",
       "      <td>0.989473</td>\n",
       "      <td>0.999986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zzc_score</th>\n",
       "      <td>float64</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.00%</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.500627</td>\n",
       "      <td>0.289067</td>\n",
       "      <td>1.15778e-05</td>\n",
       "      <td>0.0101856</td>\n",
       "      <td>0.0990114</td>\n",
       "      <td>0.501688</td>\n",
       "      <td>0.750986</td>\n",
       "      <td>0.899924</td>\n",
       "      <td>0.990043</td>\n",
       "      <td>0.999998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zcx_score</th>\n",
       "      <td>float64</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.00%</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.499672</td>\n",
       "      <td>0.289137</td>\n",
       "      <td>9.97767e-06</td>\n",
       "      <td>0.0103249</td>\n",
       "      <td>0.0997429</td>\n",
       "      <td>0.49913</td>\n",
       "      <td>0.750683</td>\n",
       "      <td>0.901942</td>\n",
       "      <td>0.989712</td>\n",
       "      <td>0.999987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>person_info</th>\n",
       "      <td>float64</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.00%</td>\n",
       "      <td>7</td>\n",
       "      <td>-0.078229</td>\n",
       "      <td>0.156859</td>\n",
       "      <td>-0.322581</td>\n",
       "      <td>-0.322581</td>\n",
       "      <td>-0.322581</td>\n",
       "      <td>-0.0537176</td>\n",
       "      <td>0.078853</td>\n",
       "      <td>0.078853</td>\n",
       "      <td>0.078853</td>\n",
       "      <td>0.078853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>finance_info</th>\n",
       "      <td>float64</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.00%</td>\n",
       "      <td>35</td>\n",
       "      <td>0.0367625</td>\n",
       "      <td>0.0396866</td>\n",
       "      <td>0.0238095</td>\n",
       "      <td>0.0238095</td>\n",
       "      <td>0.0238095</td>\n",
       "      <td>0.0238095</td>\n",
       "      <td>0.0238095</td>\n",
       "      <td>0.0714286</td>\n",
       "      <td>0.214286</td>\n",
       "      <td>1.02381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>credit_info</th>\n",
       "      <td>float64</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.00%</td>\n",
       "      <td>100</td>\n",
       "      <td>0.0636262</td>\n",
       "      <td>0.143098</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>act_info</th>\n",
       "      <td>float64</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.00%</td>\n",
       "      <td>74</td>\n",
       "      <td>0.236197</td>\n",
       "      <td>0.157132</td>\n",
       "      <td>0.0769231</td>\n",
       "      <td>0.0769231</td>\n",
       "      <td>0.0769231</td>\n",
       "      <td>0.205128</td>\n",
       "      <td>0.346154</td>\n",
       "      <td>0.487179</td>\n",
       "      <td>0.615385</td>\n",
       "      <td>1.08974</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>samp_type</th>\n",
       "      <td>object</td>\n",
       "      <td>95806</td>\n",
       "      <td>0.00%</td>\n",
       "      <td>3</td>\n",
       "      <td>dev:68.16%</td>\n",
       "      <td>off:16.67%</td>\n",
       "      <td>val:15.16%</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>dev:68.16%</td>\n",
       "      <td>off:16.67%</td>\n",
       "      <td>val:15.16%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 type   size missing  unique     mean_or_top1     std_or_top2  \\\n",
       "bad_ind       float64  95806   0.00%       2        0.0187671        0.135702   \n",
       "uid            object  95806   0.00%   95806  A14795869:0.00%  A9676154:0.00%   \n",
       "td_score      float64  95806   0.00%   95806         0.499739        0.288349   \n",
       "jxl_score     float64  95806   0.00%   95806         0.499338         0.28885   \n",
       "mj_score      float64  95806   0.00%   95806          0.50164        0.288679   \n",
       "rh_score      float64  95806   0.00%   95806         0.498407        0.287797   \n",
       "zzc_score     float64  95806   0.00%   95806         0.500627        0.289067   \n",
       "zcx_score     float64  95806   0.00%   95806         0.499672        0.289137   \n",
       "person_info   float64  95806   0.00%       7        -0.078229        0.156859   \n",
       "finance_info  float64  95806   0.00%      35        0.0367625       0.0396866   \n",
       "credit_info   float64  95806   0.00%     100        0.0636262        0.143098   \n",
       "act_info      float64  95806   0.00%      74         0.236197        0.157132   \n",
       "samp_type      object  95806   0.00%       3       dev:68.16%      off:16.67%   \n",
       "\n",
       "                 min_or_top3       1%_or_top4     10%_or_top5  50%_or_bottom5  \\\n",
       "bad_ind                    0                0               0               0   \n",
       "uid           A8747039:0.00%  A11068305:0.00%  A3268951:0.00%  A2095231:0.00%   \n",
       "td_score         5.46966e-06       0.00961341       0.0997056        0.500719   \n",
       "jxl_score        1.28155e-05       0.00994678       0.0991025        0.499795   \n",
       "mj_score         6.92442e-06        0.0105076        0.100882        0.503048   \n",
       "rh_score         5.00212e-06       0.00991632       0.0999483        0.497466   \n",
       "zzc_score        1.15778e-05        0.0101856       0.0990114        0.501688   \n",
       "zcx_score        9.97767e-06        0.0103249       0.0997429         0.49913   \n",
       "person_info        -0.322581        -0.322581       -0.322581      -0.0537176   \n",
       "finance_info       0.0238095        0.0238095       0.0238095       0.0238095   \n",
       "credit_info                0                0               0               0   \n",
       "act_info           0.0769231        0.0769231       0.0769231        0.205128   \n",
       "samp_type         val:15.16%             None            None            None   \n",
       "\n",
       "              75%_or_bottom4   90%_or_bottom3 99%_or_bottom2  max_or_bottom1  \n",
       "bad_ind                    0                0              1               1  \n",
       "uid           A2007149:0.00%  A14790772:0.00%  A396461:0.00%  A5226432:0.00%  \n",
       "td_score            0.747984         0.900024       0.990041        0.999999  \n",
       "jxl_score           0.748646         0.899703       0.989348        0.999985  \n",
       "mj_score            0.752032         0.899308       0.990047        0.999993  \n",
       "rh_score            0.747188         0.899286       0.989473        0.999986  \n",
       "zzc_score           0.750986         0.899924       0.990043        0.999998  \n",
       "zcx_score           0.750683         0.901942       0.989712        0.999987  \n",
       "person_info         0.078853         0.078853       0.078853        0.078853  \n",
       "finance_info       0.0238095        0.0714286       0.214286         1.02381  \n",
       "credit_info             0.06             0.18            0.8               1  \n",
       "act_info            0.346154         0.487179       0.615385         1.08974  \n",
       "samp_type               None       dev:68.16%     off:16.67%      val:15.16%  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toad.detector.detect(data_all)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5.特征剔除"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "keep: 12 drop empty: 0 drop iv: 1 drop corr: 0\n"
     ]
    }
   ],
   "source": [
    "dev_slct1, drop_lst = toad.selection.select(dev, dev['bad_ind'], \n",
    "                                            empty=0.7, iv=0.03, \n",
    "                                            corr=1, \n",
    "                                            return_drop=True, \n",
    "                                            exclude=ex_list)\n",
    "\n",
    "print('keep:', dev_slct1.shape[1], \n",
    "      'drop empty:', len(drop_lst['empty']), \n",
    "      'drop iv:', len(drop_lst['iv']), \n",
    "      'drop corr:', len(drop_lst['corr']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "6.卡方分箱"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'td_score': [0.7989831262724624], 'jxl_score': [0.4197048501965005], 'mj_score': [0.3615303943747963], 'zzc_score': [0.4469861520889339], 'zcx_score': [0.7007847486465795], 'person_info': [-0.2610139784946237, -0.1286774193548387, -0.05371756272401434, 0.013863440860215051, 0.06266021505376344, 0.07885304659498207], 'finance_info': [0.047619047619047616], 'credit_info': [0.02, 0.04, 0.11], 'act_info': [0.1153846153846154, 0.14102564102564102, 0.16666666666666666, 0.20512820512820512, 0.2692307692307692, 0.35897435897435903, 0.3974358974358974, 0.5256410256410257]}\n"
     ]
    }
   ],
   "source": [
    "# 得到切分节点\n",
    "combiner = toad.transform.Combiner()\n",
    "combiner.fit(dev_slct1, dev_slct1['bad_ind'], method='chi', \n",
    "             min_samples=0.05, exclude=ex_list)\n",
    "# 导出箱的节点\n",
    "bins = combiner.export()\n",
    "print(bins)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "7.分箱效果图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='act_info', ylabel='prop'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 根据节点实施分箱\n",
    "dev_slct2 = combiner.transform(dev_slct1)\n",
    "val2 = combiner.transform(val[dev_slct1.columns])\n",
    "off2 = combiner.transform(off[dev_slct1.columns])\n",
    "# 分箱后通过画图观察\n",
    "bin_plot(dev_slct2, x='act_info', target='bad_ind')\n",
    "bin_plot(val2, x='act_info', target='bad_ind')\n",
    "bin_plot(off2, x='act_info', target='bad_ind')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.1153846153846154,\n",
       " 0.14102564102564102,\n",
       " 0.16666666666666666,\n",
       " 0.20512820512820512,\n",
       " 0.2692307692307692,\n",
       " 0.35897435897435903,\n",
       " 0.3974358974358974,\n",
       " 0.5256410256410257]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看单箱节点\n",
    "bins['act_info']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='act_info', ylabel='prop'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 只保留需要的两个分割点，并重新画出Bivar图\n",
    "adj_bin = {'act_info': [0.16666666666666666, 0.35897435897435903,]}\n",
    "combiner.set_rules(adj_bin)\n",
    "\n",
    "dev_slct3 = combiner.transform(dev_slct1)\n",
    "val3 = combiner.transform(val[dev_slct1.columns])\n",
    "off3 = combiner.transform(off[dev_slct1.columns])\n",
    "\n",
    "# 画出\n",
    "bin_plot(dev_slct3, x='act_info', target='bad_ind')\n",
    "bin_plot(val3, x='act_info', target='bad_ind')\n",
    "bin_plot(off3, x='act_info', target='bad_ind')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "8.绘制负样本占比关联图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='samp_type', ylabel='badrate'>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 无错位\n",
    "data = pd.concat([dev_slct3, val3, off3], join='inner')\n",
    "badrate_plot(data, x='samp_type', target='bad_ind', by='person_info')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "9.WOE编码"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = toad.transform.WOETransformer()\n",
    "dev_slct2_woe = t.fit_transform(dev_slct3, dev_slct3['bad_ind'], exclude=ex_list)\n",
    "val_woe = t.transform(val3[dev_slct3.columns])\n",
    "off_woe = t.transform(off3[dev_slct3.columns])\n",
    "data = pd.concat([dev_slct2_woe, val_woe, off_woe])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "计算训练集与时间外验证样本的PSI，删除PSI大于0.13的特征。注意，通过单个特征的PSI值建议在0.02以下，根据具体情况可以适当调整。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "10.筛选PSI值小于0.13的值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(95806, 11)\n"
     ]
    }
   ],
   "source": [
    "psi_df = toad.metrics.PSI(dev_slct2_woe, val_woe).sort_values(0)\n",
    "psi_df = psi_df.reset_index()\n",
    "psi_df.columns = ['feature', 'psi']\n",
    "psi_013 = list(psi_df[psi_df.psi<0.13].feature)\n",
    "for i in ex_list:\n",
    "    if i in psi_013:\n",
    "        pass\n",
    "    else:\n",
    "        psi_013.append(i)\n",
    "data = data[psi_013]\n",
    "dev_woe_psi = dev_slct2_woe[psi_013]\n",
    "val_woe_psi = val_woe[psi_013]\n",
    "off_woe_psi = off_woe[psi_013]\n",
    "print(data.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "11.重新选择特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "keep: 7 drop empty: 0 drop iv: 4 drop corr: 0\n"
     ]
    }
   ],
   "source": [
    "dev_woe_psi2, drop_lst = toad.selection.select(dev_woe_psi, \n",
    "                                               dev_woe_psi['bad_ind'], \n",
    "                                               empty=0.6, \n",
    "                                               iv=0.001, \n",
    "                                               corr=0.5, \n",
    "                                               return_drop=True, \n",
    "                                               exclude=ex_list)\n",
    "\n",
    "print('keep:', dev_woe_psi2.shape[1], \n",
    "      'drop empty:', len(drop_lst['empty']), \n",
    "      'drop iv:', len(drop_lst['iv']), \n",
    "      'drop corr:', len(drop_lst['corr']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "12.逐步回归"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(95806, 6)\n"
     ]
    }
   ],
   "source": [
    "dev_woe_psi_stp = toad.selection.stepwise(dev_woe_psi2, \n",
    "                                          dev_woe_psi2['bad_ind'], \n",
    "                                          exclude=ex_list, \n",
    "                                          direction='both', \n",
    "                                          criterion='aic', \n",
    "                                          estimator='ols', \n",
    "                                          intercept=False)\n",
    "\n",
    "val_woe_psi_stp = val_woe_psi[dev_woe_psi_stp.columns]\n",
    "off_woe_psi_stp = off_woe_psi[dev_woe_psi_stp.columns]\n",
    "data = pd.concat([dev_woe_psi_stp, val_woe_psi_stp, off_woe_psi_stp])\n",
    "print(data.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "13.模型训练"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "13.1.定义逻辑回归函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "def lr_model(x, y, valx, valy, offx, offy, C):\n",
    "    model = LogisticRegression(C=C, class_weight='balanced')\n",
    "    model.fit(x, y)\n",
    "    \n",
    "    y_pred = model.predict_proba(x)[:,1]\n",
    "    fpr_dev, tpr_dev, _ = roc_curve(y, y_pred)\n",
    "    train_ks = abs(fpr_dev - tpr_dev).max()\n",
    "    print('train_ks: ', train_ks)\n",
    "    \n",
    "    y_pred = model.predict_proba(valx)[:,1]\n",
    "    fpr_val, tpr_val, _ = roc_curve(valy, y_pred)\n",
    "    val_ks = abs(fpr_val - tpr_val).max()\n",
    "    print('val_ks: ', val_ks)\n",
    "    \n",
    "    y_pred = model.predict_proba(offx)[:,1]\n",
    "    fpr_off, tpr_off, _ = roc_curve(offy, y_pred)\n",
    "    off_ks = abs(fpr_off - tpr_off).max()\n",
    "    print('off_ks: ', off_ks)\n",
    "    \n",
    "    plt.plot(fpr_dev, tpr_dev, label='dev')\n",
    "    plt.plot(fpr_val, tpr_val, label='val')\n",
    "    plt.plot(fpr_off, tpr_off, label='off')\n",
    "    plt.plot([0,1], [0,1], 'k--')\n",
    "    plt.xlabel('False positive rate')\n",
    "    plt.ylabel('True positive rate')\n",
    "    plt.title('ROC Curve')\n",
    "    plt.legend(loc='best')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "13.2.定义XGBoost函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def xgb_model(x, y, valx, valy, offx, offy):\n",
    "    model = xgb.XGBClassifier(learning_rate=0.05, \n",
    "                              n_estimators=400, \n",
    "                              max_depth=2, \n",
    "                              class_weight='balanced', \n",
    "                              min_child_weight=1, \n",
    "                              subsample=1, \n",
    "                              nthread=-1,\n",
    "                              scale_pos_weight=1, \n",
    "                              random_state=1, \n",
    "                              n_jobs=-1, \n",
    "                              reg_lambda=300)\n",
    "    model.fit(x, y)\n",
    "    \n",
    "    y_pred = model.predict_proba(x)[:,1]\n",
    "    fpr_dev, tpr_dev, _ = roc_curve(y, y_pred)\n",
    "    train_ks = abs(fpr_dev - tpr_dev).max()\n",
    "    print('train_ks: ', train_ks)\n",
    "    \n",
    "    y_pred = model.predict_proba(valx)[:,1]\n",
    "    fpr_val, tpr_val, _ = roc_curve(valy, y_pred)\n",
    "    val_ks = abs(fpr_val - tpr_val).max()\n",
    "    print('val_ks: ', val_ks)\n",
    "    \n",
    "    y_pred = model.predict_proba(offx)[:,1]\n",
    "    fpr_off, tpr_off, _ = roc_curve(offy, y_pred)\n",
    "    off_ks = abs(fpr_off - tpr_off).max()\n",
    "    print('off_ks: ', off_ks)\n",
    "    \n",
    "    plt.plot(fpr_dev, tpr_dev, label='dev')\n",
    "    plt.plot(fpr_val, tpr_val, label='val')\n",
    "    plt.plot(fpr_off, tpr_off, label='off')\n",
    "    plt.plot([0,1], [0,1], 'k--')\n",
    "    plt.xlabel('False positive rate')\n",
    "    plt.ylabel('True positive rate')\n",
    "    plt.title('ROC Curve')\n",
    "    plt.legend(loc='best')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "13.3.调用模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "def bi_train(data, dep='bad_ind', exclude=None):\n",
    "    std_scaler = StandardScaler()\n",
    "    # 变量名\n",
    "    lis = data.columns.tolist()\n",
    "    for i in exclude:\n",
    "        lis.remove(i)\n",
    "    data[lis] = std_scaler.fit_transform(data[lis])\n",
    "    devv = data[(data['samp_type'] == 'dev')]\n",
    "    vall = data[(data['samp_type'] == 'val')]\n",
    "    offf = data[(data['samp_type'] == 'off')]\n",
    "    x, y = devv[lis], devv[dep]\n",
    "    valx, valy = vall[lis], vall[dep]\n",
    "    offx, offy = offf[lis], offf[dep]\n",
    "    # 逻辑回归正向\n",
    "    print('逻辑回归正向：')\n",
    "    lr_model(x, y, valx, valy, offx, offy, 0.1)\n",
    "    # 逻辑回归反向\n",
    "    print('逻辑回归反向：')\n",
    "    lr_model(offx, offy, valx, valy, x, y, 0.1)\n",
    "    # XGBoost正向\n",
    "    print('XGBoost正向：')\n",
    "    xgb_model(x, y, valx, valy, offx, offy)\n",
    "    # XGBoost反向\n",
    "    xgb_model(offx, offy, valx, valy, x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "逻辑回归正向：\n",
      "train_ks:  0.41733648227995124\n",
      "train_ks:  0.3593935758405114\n",
      "train_ks:  0.3758086175640308\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "逻辑回归反向：\n",
      "train_ks:  0.3892612859630226\n",
      "train_ks:  0.3717891855920369\n",
      "train_ks:  0.4061965880072622\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "XGBoost正向：\n",
      "[23:20:46] WARNING: C:\\Users\\Administrator\\workspace\\xgboost-win64_release_1.2.0\\src\\learner.cc:516: \n",
      "Parameters: { class_weight } might not be used.\n",
      "\n",
      "  This may not be accurate due to some parameters are only used in language bindings but\n",
      "  passed down to XGBoost core.  Or some parameters are not used but slip through this\n",
      "  verification. Please open an issue if you find above cases.\n",
      "\n",
      "\n",
      "train_ks:  0.42521927400747045\n",
      "train_ks:  0.3595542266920359\n",
      "train_ks:  0.37437103192850807\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[23:20:48] WARNING: C:\\Users\\Administrator\\workspace\\xgboost-win64_release_1.2.0\\src\\learner.cc:516: \n",
      "Parameters: { class_weight } might not be used.\n",
      "\n",
      "  This may not be accurate due to some parameters are only used in language bindings but\n",
      "  passed down to XGBoost core.  Or some parameters are not used but slip through this\n",
      "  verification. Please open an issue if you find above cases.\n",
      "\n",
      "\n",
      "train_ks:  0.3939473708822855\n",
      "train_ks:  0.3799497614606668\n",
      "train_ks:  0.3936270948436908\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bi_train(data, dep='bad_ind', exclude=ex_list)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "14.单个逻辑回归模型进行拟合"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "使用默认参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LogisticRegression()"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dep = 'bad_ind'  \n",
    "lis = list(data.columns)  \n",
    "for i in ex_list:  \n",
    "    lis.remove(i)\n",
    "devv = data[data['samp_type']=='dev']\n",
    "vall = data[data['samp_type']=='val']\n",
    "offf = data[data['samp_type']=='off' ]\n",
    "x, y = devv[lis], devv[dep]  \n",
    "valx, valy = vall[lis], vall[dep]\n",
    "offx, offy = offf[lis], offf[dep]\n",
    "lr = LogisticRegression()  \n",
    "lr.fit(x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "15.计算F1分数、KS值和AUC值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "训练集\n",
      "F1: 0.02962459026532253\n",
      "KS: 0.41406129833591426\n",
      "AUC: 0.7713247123864264\n",
      "跨时间\n",
      "F1: 0.027689429373246022\n",
      "KS: 0.36127808343721585\n",
      "AUC: 0.7225727568398459\n",
      "跨时间\n",
      "F1: 0.032454090150250414\n",
      "KS: 0.3807135163445966\n",
      "AUC: 0.7435613582904539\n"
     ]
    }
   ],
   "source": [
    "prob_dev = lr.predict_proba(x)[:,1]  \n",
    "print('训练集')  \n",
    "print('F1:', F1(prob_dev,y))  \n",
    "print('KS:', KS(prob_dev,y))  \n",
    "print('AUC:', AUC(prob_dev,y)) \n",
    "\n",
    "prob_val = lr.predict_proba(valx)[:,1]  \n",
    "print('跨时间')  \n",
    "print('F1:', F1(prob_val,valy))  \n",
    "print('KS:', KS(prob_val,valy))  \n",
    "print('AUC:', AUC(prob_val,valy)) \n",
    "\n",
    "prob_off = lr.predict_proba(offx)[:,1]  \n",
    "print('跨时间')  \n",
    "print('F1:', F1(prob_off,offy))  \n",
    "print('KS:', KS(prob_off,offy))  \n",
    "print('AUC:', AUC(prob_off,offy))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从两个角度衡量稳定性，分别计算模型PSI和单变量PSI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "模型PSI: 0.34091667386100255\n",
      "特征PSI: \n",
      " credit_info    0.098585\n",
      "act_info       0.124820\n",
      "person_info    0.127833\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print('模型PSI:',toad.metrics.PSI(prob_dev,prob_off))  \n",
    "print('特征PSI:','\\n',toad.metrics.PSI(x,offx).sort_values(0)) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "生成模型时间外样本的KS报告"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>min</th>\n",
       "      <th>max</th>\n",
       "      <th>bads</th>\n",
       "      <th>goods</th>\n",
       "      <th>total</th>\n",
       "      <th>bad_rate</th>\n",
       "      <th>good_rate</th>\n",
       "      <th>odds</th>\n",
       "      <th>bad_prop</th>\n",
       "      <th>good_prop</th>\n",
       "      <th>...</th>\n",
       "      <th>cum_bad_rate</th>\n",
       "      <th>cum_bad_rate_rev</th>\n",
       "      <th>cum_bads_prop</th>\n",
       "      <th>cum_bads_prop_rev</th>\n",
       "      <th>cum_goods_prop</th>\n",
       "      <th>cum_goods_prop_rev</th>\n",
       "      <th>cum_total_prop</th>\n",
       "      <th>cum_total_prop_rev</th>\n",
       "      <th>ks</th>\n",
       "      <th>lift</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.001870</td>\n",
       "      <td>0.003791</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1256.0</td>\n",
       "      <td>1259.0</td>\n",
       "      <td>0.002383</td>\n",
       "      <td>0.997617</td>\n",
       "      <td>0.002389</td>\n",
       "      <td>0.009146</td>\n",
       "      <td>0.080271</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002383</td>\n",
       "      <td>0.020532</td>\n",
       "      <td>0.009146</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.080271</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.078811</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.071125</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.003968</td>\n",
       "      <td>0.005382</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1554.0</td>\n",
       "      <td>1557.0</td>\n",
       "      <td>0.001927</td>\n",
       "      <td>0.998073</td>\n",
       "      <td>0.001931</td>\n",
       "      <td>0.009146</td>\n",
       "      <td>0.099316</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002131</td>\n",
       "      <td>0.022085</td>\n",
       "      <td>0.018293</td>\n",
       "      <td>0.990854</td>\n",
       "      <td>0.179587</td>\n",
       "      <td>0.919729</td>\n",
       "      <td>0.176275</td>\n",
       "      <td>0.921189</td>\n",
       "      <td>0.161294</td>\n",
       "      <td>1.075624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.006361</td>\n",
       "      <td>0.008708</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1840.0</td>\n",
       "      <td>1850.0</td>\n",
       "      <td>0.005405</td>\n",
       "      <td>0.994595</td>\n",
       "      <td>0.005435</td>\n",
       "      <td>0.030488</td>\n",
       "      <td>0.117594</td>\n",
       "      <td>...</td>\n",
       "      <td>0.003429</td>\n",
       "      <td>0.024470</td>\n",
       "      <td>0.048780</td>\n",
       "      <td>0.981707</td>\n",
       "      <td>0.297182</td>\n",
       "      <td>0.820413</td>\n",
       "      <td>0.292081</td>\n",
       "      <td>0.823725</td>\n",
       "      <td>0.248401</td>\n",
       "      <td>1.191791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.008728</td>\n",
       "      <td>0.010891</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1258.0</td>\n",
       "      <td>1270.0</td>\n",
       "      <td>0.009449</td>\n",
       "      <td>0.990551</td>\n",
       "      <td>0.009539</td>\n",
       "      <td>0.036585</td>\n",
       "      <td>0.080399</td>\n",
       "      <td>...</td>\n",
       "      <td>0.004717</td>\n",
       "      <td>0.027589</td>\n",
       "      <td>0.085366</td>\n",
       "      <td>0.951220</td>\n",
       "      <td>0.377580</td>\n",
       "      <td>0.702818</td>\n",
       "      <td>0.371581</td>\n",
       "      <td>0.707919</td>\n",
       "      <td>0.292215</td>\n",
       "      <td>1.343685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.011006</td>\n",
       "      <td>0.017980</td>\n",
       "      <td>27.0</td>\n",
       "      <td>2004.0</td>\n",
       "      <td>2031.0</td>\n",
       "      <td>0.013294</td>\n",
       "      <td>0.986706</td>\n",
       "      <td>0.013473</td>\n",
       "      <td>0.082317</td>\n",
       "      <td>0.128076</td>\n",
       "      <td>...</td>\n",
       "      <td>0.006903</td>\n",
       "      <td>0.029883</td>\n",
       "      <td>0.167683</td>\n",
       "      <td>0.914634</td>\n",
       "      <td>0.505656</td>\n",
       "      <td>0.622420</td>\n",
       "      <td>0.498717</td>\n",
       "      <td>0.628419</td>\n",
       "      <td>0.337973</td>\n",
       "      <td>1.455452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.018032</td>\n",
       "      <td>0.018032</td>\n",
       "      <td>0.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.002620</td>\n",
       "      <td>...</td>\n",
       "      <td>0.006868</td>\n",
       "      <td>0.034091</td>\n",
       "      <td>0.167683</td>\n",
       "      <td>0.832317</td>\n",
       "      <td>0.508276</td>\n",
       "      <td>0.494344</td>\n",
       "      <td>0.501283</td>\n",
       "      <td>0.501283</td>\n",
       "      <td>0.340593</td>\n",
       "      <td>1.660373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.018379</td>\n",
       "      <td>0.029245</td>\n",
       "      <td>62.0</td>\n",
       "      <td>3101.0</td>\n",
       "      <td>3163.0</td>\n",
       "      <td>0.019602</td>\n",
       "      <td>0.980398</td>\n",
       "      <td>0.019994</td>\n",
       "      <td>0.189024</td>\n",
       "      <td>0.198185</td>\n",
       "      <td>...</td>\n",
       "      <td>0.010474</td>\n",
       "      <td>0.034266</td>\n",
       "      <td>0.356707</td>\n",
       "      <td>0.832317</td>\n",
       "      <td>0.706461</td>\n",
       "      <td>0.491724</td>\n",
       "      <td>0.699280</td>\n",
       "      <td>0.498717</td>\n",
       "      <td>0.349754</td>\n",
       "      <td>1.668917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.029886</td>\n",
       "      <td>0.037582</td>\n",
       "      <td>41.0</td>\n",
       "      <td>1435.0</td>\n",
       "      <td>1476.0</td>\n",
       "      <td>0.027778</td>\n",
       "      <td>0.972222</td>\n",
       "      <td>0.028571</td>\n",
       "      <td>0.125000</td>\n",
       "      <td>0.091711</td>\n",
       "      <td>...</td>\n",
       "      <td>0.012493</td>\n",
       "      <td>0.043922</td>\n",
       "      <td>0.481707</td>\n",
       "      <td>0.643293</td>\n",
       "      <td>0.798172</td>\n",
       "      <td>0.293539</td>\n",
       "      <td>0.791674</td>\n",
       "      <td>0.300720</td>\n",
       "      <td>0.316465</td>\n",
       "      <td>2.139176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.037968</td>\n",
       "      <td>0.058339</td>\n",
       "      <td>43.0</td>\n",
       "      <td>1007.0</td>\n",
       "      <td>1050.0</td>\n",
       "      <td>0.040952</td>\n",
       "      <td>0.959048</td>\n",
       "      <td>0.042701</td>\n",
       "      <td>0.131098</td>\n",
       "      <td>0.064357</td>\n",
       "      <td>...</td>\n",
       "      <td>0.014675</td>\n",
       "      <td>0.051082</td>\n",
       "      <td>0.612805</td>\n",
       "      <td>0.518293</td>\n",
       "      <td>0.862530</td>\n",
       "      <td>0.201828</td>\n",
       "      <td>0.857402</td>\n",
       "      <td>0.208326</td>\n",
       "      <td>0.249725</td>\n",
       "      <td>2.487898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.062269</td>\n",
       "      <td>0.094398</td>\n",
       "      <td>127.0</td>\n",
       "      <td>2151.0</td>\n",
       "      <td>2278.0</td>\n",
       "      <td>0.055751</td>\n",
       "      <td>0.944249</td>\n",
       "      <td>0.059042</td>\n",
       "      <td>0.387195</td>\n",
       "      <td>0.137470</td>\n",
       "      <td>...</td>\n",
       "      <td>0.020532</td>\n",
       "      <td>0.055751</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.387195</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.137470</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.142598</td>\n",
       "      <td>-0.000000</td>\n",
       "      <td>2.715295</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        min       max   bads   goods   total  bad_rate  good_rate      odds  \\\n",
       "0  0.001870  0.003791    3.0  1256.0  1259.0  0.002383   0.997617  0.002389   \n",
       "1  0.003968  0.005382    3.0  1554.0  1557.0  0.001927   0.998073  0.001931   \n",
       "2  0.006361  0.008708   10.0  1840.0  1850.0  0.005405   0.994595  0.005435   \n",
       "3  0.008728  0.010891   12.0  1258.0  1270.0  0.009449   0.990551  0.009539   \n",
       "4  0.011006  0.017980   27.0  2004.0  2031.0  0.013294   0.986706  0.013473   \n",
       "5  0.018032  0.018032    0.0    41.0    41.0  0.000000   1.000000  0.000000   \n",
       "6  0.018379  0.029245   62.0  3101.0  3163.0  0.019602   0.980398  0.019994   \n",
       "7  0.029886  0.037582   41.0  1435.0  1476.0  0.027778   0.972222  0.028571   \n",
       "8  0.037968  0.058339   43.0  1007.0  1050.0  0.040952   0.959048  0.042701   \n",
       "9  0.062269  0.094398  127.0  2151.0  2278.0  0.055751   0.944249  0.059042   \n",
       "\n",
       "   bad_prop  good_prop  ...  cum_bad_rate  cum_bad_rate_rev  cum_bads_prop  \\\n",
       "0  0.009146   0.080271  ...      0.002383          0.020532       0.009146   \n",
       "1  0.009146   0.099316  ...      0.002131          0.022085       0.018293   \n",
       "2  0.030488   0.117594  ...      0.003429          0.024470       0.048780   \n",
       "3  0.036585   0.080399  ...      0.004717          0.027589       0.085366   \n",
       "4  0.082317   0.128076  ...      0.006903          0.029883       0.167683   \n",
       "5  0.000000   0.002620  ...      0.006868          0.034091       0.167683   \n",
       "6  0.189024   0.198185  ...      0.010474          0.034266       0.356707   \n",
       "7  0.125000   0.091711  ...      0.012493          0.043922       0.481707   \n",
       "8  0.131098   0.064357  ...      0.014675          0.051082       0.612805   \n",
       "9  0.387195   0.137470  ...      0.020532          0.055751       1.000000   \n",
       "\n",
       "   cum_bads_prop_rev  cum_goods_prop  cum_goods_prop_rev  cum_total_prop  \\\n",
       "0           1.000000        0.080271            1.000000        0.078811   \n",
       "1           0.990854        0.179587            0.919729        0.176275   \n",
       "2           0.981707        0.297182            0.820413        0.292081   \n",
       "3           0.951220        0.377580            0.702818        0.371581   \n",
       "4           0.914634        0.505656            0.622420        0.498717   \n",
       "5           0.832317        0.508276            0.494344        0.501283   \n",
       "6           0.832317        0.706461            0.491724        0.699280   \n",
       "7           0.643293        0.798172            0.293539        0.791674   \n",
       "8           0.518293        0.862530            0.201828        0.857402   \n",
       "9           0.387195        1.000000            0.137470        1.000000   \n",
       "\n",
       "   cum_total_prop_rev        ks      lift  \n",
       "0            1.000000  0.071125  1.000000  \n",
       "1            0.921189  0.161294  1.075624  \n",
       "2            0.823725  0.248401  1.191791  \n",
       "3            0.707919  0.292215  1.343685  \n",
       "4            0.628419  0.337973  1.455452  \n",
       "5            0.501283  0.340593  1.660373  \n",
       "6            0.498717  0.349754  1.668917  \n",
       "7            0.300720  0.316465  2.139176  \n",
       "8            0.208326  0.249725  2.487898  \n",
       "9            0.142598 -0.000000  2.715295  \n",
       "\n",
       "[10 rows x 21 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toad.metrics.KS_bucket(prob_off,offy,\n",
    "                       bucket=10,\n",
    "                       method='quantile') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "制作评分卡"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>value</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>credit_info</td>\n",
       "      <td>[-inf ~ 0.02)</td>\n",
       "      <td>158.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>credit_info</td>\n",
       "      <td>[0.02 ~ 0.04)</td>\n",
       "      <td>122.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>credit_info</td>\n",
       "      <td>[0.04 ~ 0.11)</td>\n",
       "      <td>73.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>credit_info</td>\n",
       "      <td>[0.11 ~ inf)</td>\n",
       "      <td>43.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>act_info</td>\n",
       "      <td>[-inf ~ 0.16666666666666666)</td>\n",
       "      <td>94.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>act_info</td>\n",
       "      <td>[0.16666666666666666 ~ 0.35897435897435903)</td>\n",
       "      <td>115.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>act_info</td>\n",
       "      <td>[0.35897435897435903 ~ inf)</td>\n",
       "      <td>125.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>person_info</td>\n",
       "      <td>[-inf ~ -0.2610139784946237)</td>\n",
       "      <td>172.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>person_info</td>\n",
       "      <td>[-0.2610139784946237 ~ -0.1286774193548387)</td>\n",
       "      <td>142.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>person_info</td>\n",
       "      <td>[-0.1286774193548387 ~ -0.05371756272401434)</td>\n",
       "      <td>123.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>person_info</td>\n",
       "      <td>[-0.05371756272401434 ~ 0.013863440860215051)</td>\n",
       "      <td>120.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>person_info</td>\n",
       "      <td>[0.013863440860215051 ~ 0.06266021505376344)</td>\n",
       "      <td>108.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>person_info</td>\n",
       "      <td>[0.06266021505376344 ~ 0.07885304659498207)</td>\n",
       "      <td>90.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>person_info</td>\n",
       "      <td>[0.07885304659498207 ~ inf)</td>\n",
       "      <td>75.46</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           name                                          value   score\n",
       "0   credit_info                                  [-inf ~ 0.02)  158.04\n",
       "1   credit_info                                  [0.02 ~ 0.04)  122.51\n",
       "2   credit_info                                  [0.04 ~ 0.11)   73.94\n",
       "3   credit_info                                   [0.11 ~ inf)   43.98\n",
       "4      act_info                   [-inf ~ 0.16666666666666666)   94.24\n",
       "5      act_info    [0.16666666666666666 ~ 0.35897435897435903)  115.71\n",
       "6      act_info                    [0.35897435897435903 ~ inf)  125.38\n",
       "7   person_info                   [-inf ~ -0.2610139784946237)  172.76\n",
       "8   person_info    [-0.2610139784946237 ~ -0.1286774193548387)  142.93\n",
       "9   person_info   [-0.1286774193548387 ~ -0.05371756272401434)  123.74\n",
       "10  person_info  [-0.05371756272401434 ~ 0.013863440860215051)  120.79\n",
       "11  person_info   [0.013863440860215051 ~ 0.06266021505376344)  108.83\n",
       "12  person_info    [0.06266021505376344 ~ 0.07885304659498207)   90.32\n",
       "13  person_info                    [0.07885304659498207 ~ inf)   75.46"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "card = ScoreCard(combiner=combiner, \n",
    "                    transer=t, C=0.1, \n",
    "                    class_weight='balanced', \n",
    "                    base_score=600,\n",
    "                    base_odds=35,\n",
    "                    pdo=60,\n",
    "                    rate=2)  \n",
    "card.fit(x,y)  \n",
    "final_card = card.export(to_frame=True)  \n",
    "final_card"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:lkm]",
   "language": "python",
   "name": "lkm"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
